Fiber Optic Sensor Research Articles

Fiber Optic Sensor Coated with Multiple Layers of Hexagonal Boron Nitride Nanosheets (BNNS) for the Detection of Volatile Organic Compounds.

Nowadays, volatile organic compound (VOC) detection is imperative to ensure environmental safety in industry and indoor environments, as well as to monitor human health in medical diagnosis. Gas sensors with the best sensor response, selectivity, and stability are in high demand. Simultaneously, the advancement of nanotechnology facilitates novel nanomaterial-based gas sensors with superior sensor characteristics and low power consumption. Recently, boron nitride, a 2D material, has emerged as an excellent candidate for gas sensing and demonstrated exceptional sensing characteristics for new-generation gas sensing devices. Herein, ultrathin porous boron nitride nanosheets (BNNSs) with large lateral sizes were synthesized using a facile synthesis approach, and their material characteristics were investigated utilizing a variety of analytical techniques, including X-ray diffraction, Fourier transform infrared spectroscopy, ultraviolet spectroscopy, X-ray photoelectron spectroscopy, and scanning electron microscopy. A BNNS-coated cladding-modified fiber optic sensor (FOS) probe was prepared and employed for VOC (ammonia, ethanol, and acetone) sensing across concentrations varying from 0 to 300 ppm. The BNNSs-coated FOS demonstrated better selectivity toward 300 ppm ammonia, and specifically annealed BNNSs displayed a maximum sensor response of 55% along with a response/recovery times of 15 s/34 s compared to its counterparts. The superior ammonia sensing performances could be attributed to the formation of ultrathin nanosheets and a porous surface with slit-like features in hexagonal boron nitride.

Discharge splicing-free ultra-highly sensitive fiber-optic temperature sensor based on PDMS and the Vernier effect

A novel discharge splicing-free ultra-highly sensitive fiber-optic temperature sensor, based on polydimethylsiloxane (PMDS) and the Vernier effect, is constructed and experimentally validated. The sensor comprises single mode fiber (SMF), hollow core fiber (HCF), and PDMS. The Vernier effect is produced by the PDMS cavity and the mixed PDMS-air cavity during fabrication. By virtue of the Vernier effect and the temperature-sensitive material PDMS, this sensor shows an exceptionally high temperature sensitivity of −4.08658 nm/℃ while maintaining an outstanding linearity of 0.99972. The repeatability and stability have been demonstrated by subjecting the sensor to three cycles of heating and cooling, each with a 24-hour interval. Furthermore, experimental results indicate that the sensor exhibits excellent resistance to microvibrations and the interference occurs inside the structure, enabling its reliable operation in harsh environments without additional package. The miniature fiber temperature sensor is easily fabricated, highly sensitive, and demonstrates exceptional stability and repeatability, serving an ideal alternative for measuring temperature in challenging conditions.

A solid-state sensor based on nanosilica/methylcellulose composite and chromoionophore 8-carboxamidoquinoline derivative as an optode pellet for Zinc(II) ion

Zinc is known to play a central role in the immune system that creates a resistance barrier against viral infection. A naked-eye zinc(II) (Zn2+) ion sensor of 2-oxo-2-(quinolin-8-ylamino)acetic acid (OQAA) as a recognition probe was designed and synthesized. By inserting functional groups of amide and carboxylic acid into a conjugated molecule of 8-aminoquinoline, Zn2+ ion (borderline acid) coordinated favorably with aromatic nitrogen atoms (borderline bases) and N-amide. Characterization of OQAA was done by FTIR, 1H NMR, 13C NMR, UV–vis, and ESI-MS. The Zn2+ ion chemosensor was fabricated by immobilizing OQAA chromogenic ionophore onto a nanosilica/methylcellulose (Si/MC) composite pellet to form a solid-state pellet sensor. A distinguishable color change from pale light-yellow to yellowish-brown of the optode pellet was observed in the presence of Zn2+ ions. Optimization of the pellet-based Zn2+ ion sensor was carried out with a fiber optic reflectance spectrophotometer at 0.25 M OQAA in tris buffer (pH 7.4). The optical fiber sensor demonstrated a linear reflectance response between 0.8 M and 2.4 M Zn2+ ion (R²=0.9741) at λmax=635 nm with a limit of detection (LOD) of 3.6 × 10−2 M and response time of 5 min. The reflectance sensor exhibited good selectivity towards Zn2+ ion over other competitive heavy metals e.g., iron(II) (Fe2+), nickel(II) (Ni2+), cobalt(II) (Co2+), copper(II)(Cu2+) and cadmium(Cd2+) ions. Additionally, the proposed Zn2+ ion sensor showed high shelf-life stability of 75 days operational duration with 80.0 % initial optical response remaining. The quick, easy, and uncomplicated preparation of the OQAA-modified Si/MC (OQAA-Si/MC) composite pellet novel material gave a reproducible reflectance signal towards the determination of Zn2+ ion concentration with a low relative standard deviation (RSD) obtained at ∼1.0 % (n=12), and was reusable three times for assay of Zn2+ ion (RSD=1.3 %). The optical chemosensor imparts remarkable color change towards the analysis of Zn2+ ions, and could offer direct and fast in-situ visual inspection of Zn2+ ion levels in complex samples without an instrument.

Detection of Track Bed Defects Based on Fibre Optic Sensor Signals and an Improved Hidden Markov Model

Railway track bed defects affect the normal operation of trains and pose great safety risks. In order to detect such issues early, we developed a railway track bed defect detection method which uses optical fibre sensors and an improved HMM (hidden Markov model) to detect the signals collected by a DAS (distributed acoustic sensing) system. First, by analysing the physical process of train operation and determining the number of hidden states, a waveform segmentation method based on average amplitude was used to solve the problem of unequal signal lengths. Second, an adaptive power spectrum energy ratio calculation method was employed to extract track fault features, a set of which was constructed by combining various quantity features. Then, normal and abnormal models were trained according to the sensor measurement area. Finally, the probability of detecting the signal with each model was compared to determine whether the signal was abnormal. Experiments were conducted to compare the applicability of the waveform segmentation method and the feature extraction method. The results show that the HMM based on both waveform segmentation and track bed defect feature sets had the highest recognition rate, the lowest number of false detection areas, and a greater impact on the signal in the early development stage of track bed defects. The proposed method, therefore, has strong recognition ability, which makes it suitable for track bed defect detection.

Pressure-Compensated Fiber-Optic Photoacoustic Sensors for Trace SO2 Analysis in Gas Insulation Equipment.

A high-sensitivity fiber-optic photoacoustic sensor with pressure compensation is proposed to analyze the decomposition component SO2 in high-pressure gas insulation equipment. The multiple influence mechanism of pressure on photoacoustic excitation and cantilever detection has been theoretically analyzed and verified. In the high-pressure environment, the excited photoacoustic signal is enhanced, which compensates for the loss of sensitivity of the cantilever. A fiber-optic F-P cantilever is utilized to simultaneously measure static pressure and dynamic photoacoustic wave, and a spectral demodulation method based on white light interference is applied to calculate the optical path difference of the F-P interferometer (FPI). The real-time pressure is judged through the linear relationship between the average optical path difference of FPI and the pressure, which gives the proposed fiber-optic photoacoustic sensor the inherent advantages of being uncharged and resistant to electromagnetic interference. The average optical path difference of FPI is positively related to pressure, with a responsivity of 0.6 μm/atm, which is based on changes in the refractive index of gas. In the range of 1-4 atm, the SO2 sensor has a higher detection sensitivity at high-pressure, which benefits from the pressure compensation effect. With the pressure environment of gas insulation equipment at 4 atm as the application background, the SO2 gas is tested. The detection limit is 20 ppb with an averaging time of 400 s.

High sensitivity Mach-Zehnder interferometric fiber-optic humidity sensor based on multimode interference enhancement

Variations in humidity can significantly disrupt the proper functioning of precision instruments and meters across various industrial, medical, and scientific applications, thereby necessitating real-time humidity monitoring. Here, a high sensitivity fiber-optic relative humidity (RH) sensor based on Mach-Zender interferometer (MZI) is proposed and demonstrated. The humidity sensor consists of single-mode fiber (SMF), peanut structure (PS), and multi-mode fiber (MMF). A multi-mode interference (MMI) enhanced fiber-optic MZI was constructed using a SMF-PS-SMF-MMF-SMF-PS-SMF cascade structure to detect small changes in the refractive index (RI) and expansion force of gelatin film caused by humidity variation. PS, as a beam splitter and combiner of MZI, provides the possibility for simple, economical, and efficient manufacturing of the fiber-based part of humidity sensors. The addition of MMF will excite higher-order core and cladding modes, laying the foundation for achieving high-sensitivity fiber-optic humidity sensors. The fiber-optic RH sensor prototype demonstrate a high sensitivity of about 0.633 nm/% RH in the RH range of 50 % RH to 80 % RH, and a low temperature cross-sensitivity of 0.165 % RH/°C. This sensor has the advantages of safe and easy manufacturing process, low manufacturing cost, and high sensitivity, providing continuous high accuracy humidity measurement results for humidity sensing in different fields.

Study by simulation and realization of a fiber optic pressure sensor based on a PDMS flexible µ-membrane

Study by simulation and realization of a fiber optic pressure sensor based on a PDMS flexible µ-membrane

Fiber Optic Devices for Diagnostics and Therapy in Photomedicine

AbstractPhotonic technologies have made enormous impacts on modern medicine, advancing disease diagnostics and treatments as well as health monitoring. A long‐standing challenge in the use of light and its widespread effects in photomedicine is the finite penetration of light in tissues. However, judiciously engineered optical fibers helped overcome this challenge and advance light delivery to deep tissues with spatial precision and desired accessibility. In recent years, the development of photonic technologies including optical biomaterials, fiber functionalization, and biomedical device innovations has greatly expanded the scope of light‐based healthcare. Here, the fundamentals and materials of fiber optics to endow themselves with biocompatibility, flexibility, and diverse functionalities required for long‐term implantation are overviewed. The design strategies of lab‐on‐fiber techniques, operation requirements to construct fiber optic sensors, and their health monitoring applications as wearable and implantable devices are presented. The use of fiber optics in major light‐based therapeutic modalities including optogenetics, photodynamic therapy, photobiomodulation, photochemical cross–linking, and photothermal therapy is illustrated to enhance their effectiveness, specificity, and feasibility. In short, a comprehensive review is provided on the fiber optic techniques and the latest photonic devices, which are envisioned to evolve photomedicine in clinical and point‐of‐care practices.

Thermal response to background leakages around an actively heated fiber optic sensor for leak detection in water distribution mains: modeling the effect of heating power and time

Fiber optic distributed temperature sensing (DTS) has been recently proposed as a promising technology to detect leaks in water infrastructure. However, it requires a suitable temperature difference between leaked water and the subsurface. Coupling active heating with fiber optic DTS could overcome this limitation, but very limited information is available on its application to leak detection in water pipelines. In this regard, this study addresses for the first time the use of active distributed temperature sensing (ADTS) to detect background leakages, ubiquitous and persistent leaks responsible for large losses and practically undetectable with conventional technologies. The 3D transient analysis of the thermal response to background leakages under different heating powers and times shows that there is potential to detect and locate incredibly small leaks (∼ L/d) with a detection threshold of 3 °C when actively heating a fiber optic sensor placed at distance from the pipe, in a location suitable for new and existing pipelines as well as for passive sensors. A potential to quantify background leakages also exists, since nonlinear relationships linking temperature alterations to the leak rate were predicted. The analysis further shows that it is crucial to determine for how long the detection threshold is overcome, and that increasing the heating power is not necessarily the answer. Finally, forced convection is the main heat transfer mechanism around the active sensor once reached by leaked water, and it appears that the chance of altering temperature and quality of water flowing within the nearby pipe and surrounding soil/groundwater would be very limited with ADTS.

Highly sensitive photonic crystal fiber optic sensor for cancer cell detection

Highly sensitive photonic crystal fiber optic sensor for cancer cell detection

Enhancing Φ-OTDR Classification Performance through Event Augmentation

As one of the research focuses in the past decades, phase sensitive optical domain reflectometer (Φ-OTDR) has come to the tipping point of its wide application. With the expansion of its application, how to classify and identify Φ-OTDR events more effectively and efficiently in practical applications has become a key and urgent issue. Over the past several years, the incorporation of machine learning methodologies has garnered considerable attention in this area. Nevertheless, the performance of those machine learning models heavily relies on the quantity and quality of the collected data. That is, the challenge of collecting rare event signals in the sensing applications strongly limits the ability of the model to classify accurately. To overcome the above weakness and further boost the capability of Ф-OTDR, we propose an event augmentation method to enhance the diversity and generalization of raw data. Experimental results show that the proposed method improves the event classification accuracy of our Ф-OTDR from 76.4% to 91.0%. The proposed method represents a promising solution to tackle with the challenges of Ф-OTDR as well as other distributed fiber optic sensors.

A case study on early-age cracking of high-strength concrete construction by coupled thermal-mechanical analysis and field monitoring

The use of high-strength concrete (HSC) in constructing high-rise reinforced concrete buildings and their deep foundations is becoming more popular because of the significant reduction in member size and, thus, self-weight in structural members. However, the higher cement content in HSC may result in increased heat of hydration and autogenous shrinkage, growing concerns about forming early-age cracks in HSC structural members. This case study assessed the early-age cracking of HSC in bored pile construction of high-rise buildings. A nonlinear transient coupled thermal-mechanical response analysis was performed to evaluate the potential of early-age cracking caused by the heat of hydration generated in the HSC using ABAQUS and two subprograms, USDFLD and UEXPAN. A 3-D finite element model was developed considering thermal effects, time-dependent evolution of early-age strength and stiffness of HSC, crack strain development, autogenous shrinkage, and stress-relaxation in the analysis. Field measurements were carried out on a 3-m diameter bored pile constructed using Grade C50/60 HSC (fck,cube = 60 MPa) for a high-rise building project in Hong Kong to evaluate the validity of the numerical model. Optical fiber sensors were used to monitor the temperature changes of the pile for approximately 380 hours after casting. The temporal and spatial temperature distributions measured in the field measurements agree well with the simulations. Large thermal gradients and high tensile stress zones were observed across the horizontal cross-sections of the pile, resulting in the formation of vertical annular cracks. Based on the results of the analysis, the maximum crack widths were predicted and compared with the durability crack width limits.

Dual-Function Wearable Hydrogel Optical Fiber for Monitoring Posture and Sweat pH.

In recent years, wearable devices have been widely used for human health monitoring. Such monitoring predominantly relies on the principles of optics and electronics. However, electronic detection is susceptible to electromagnetic interference, and traditional optical fiber detection is limited in functionality and unable to simultaneously detect both physical and chemical signals. Hence, a wearable, embedded asymmetric color-blocked optical fiber sensor based on a hydrogel has been developed. Its sensing principle is grounded in the total internal reflection within the optical fiber. The method for posture sensing involves changes in the light path due to fiber bending with color blocks providing wavelength-selective modulation by absorption changes. Sweat pH sensing is facilitated by variations in fluorescence intensity triggered by sweat-induced conformational changes in Rhodamine B. With just one fiber, it achieves both physical and chemical signal detection. Fabricated using a molding technique, this fiber boasts excellent biocompatibility and can accurately discern single and multiple bending points, with a recognition range of 0-90° for a single segment, a detection limit of 0.02 mm-1 and a sweat pH sensing linear regression R2 of 0.993, alongside great light propagation properties (-0.6 dB·cm-1). With its extensive capabilities, it holds promise for applications in medical monitoring.

Spectral Behavior of Fiber Bragg Gratings during Embedding in 3D-Printed Metal Tensile Coupons and Cyclic Loading.

Additive manufacturing (AM) enables the spatially configurable 3D integration of sensors in metal components to realize smart materials and structures. Outstanding sensing capabilities and size compatibility have made fiber optic sensors excellent candidates for integration in AM components. In this study, fiber Bragg grating (FBG) sensors were embedded in Inconel 718 tensile coupons printed using laser powder bed fusion AM. On-axis (fiber runs through the coupon's center of axis) and off-axis (fiber is at 5° and 10° to the coupon's center of axis) sensors were buried in epoxy resin inside narrow channels that run through the coupons. FBGs' spectral evolutions during embedment in the coupons were examined and cyclic loading experiments were conducted to analyze and evaluate the sensor integration process, complex strain loading, process flaws, and sensing performance. This study also demonstrates that the AM process-born deficiencies such as poor surface finish and staircase effects can be detrimental to the embedded sensors and their sensing performance.

Experimental Investigation of Low-Frequency Distributed Acoustic Sensor Responses to Two Parallel Propagating Fractures.

Low-frequency distributed acoustic sensing (LF-DAS) is a diagnostic tool for hydraulic fracture propagation with far-field monitoring using fiber optic sensors. LF-DAS senses strain rate variation caused by stress field change due to fracture propagation. Fiber optic sensors are installed in the monitoring wells in the vicinity of a fractured well. From the strain responses, fracture propagation can be evaluated. To understand subsurface conditions with multiple propagating fractures, a laboratory-scale hydraulic fracture experiment was performed simulating the LF-DAS response to fracture propagation with embedded distributed optical fiber strain sensors under these conditions. The experiment was performed using a transparent cube of epoxy with two parallel radial initial flaws centered in the cube. Fluid was injected into the sample to generate fractures along the initial flaws. The experiment used distributed high-definition fiber optic strain sensors with tight spatial resolutions. The sensors were embedded at two different locations on opposite sides of the initial flaws, serving as observation/monitoring locations. We also employed finite element modeling to numerically solve the linear elastic equations of equilibrium continuity and stress-strain relationships. The measured strains from the experiment were compared to simulation results from the finite element model. The experimentally derived strain and strain-rate waterfall plots from this study show the responses to both fractures propagating, while the fracture at the lower position took most of the fluid during the experiment. Interestingly, a fracture first began propagating from the upper flaw of the two flaws, but once the lower fracture was initiated, it grew much faster than the upper fracture. Both fibers were intercepted by the lower fracture, further verifying the strain signature as a fracture is approaching and intersecting an offset fiber.

Fiber optic strain sensor based on enhanced harmonic Vernier effect

In sensors utilizing the traditional harmonic Vernier effect, it is imperative to isolate the reference interferometer to mitigate the impact of external environmental fluctuations on the reference spectrum, thereby averting measurement inaccuracies. However, achieving such isolation between interferometers in compact fiber optic sensors poses significant challenges. We propose a fiber optic strain sensor based on the enhanced harmonic Vernier effect. In the enhanced harmonic Vernier effect, two interferometers are simultaneously involved in sensing. Hence, the isolation of interferometers is no longer a concern. Furthermore, the two interferometers exhibit responses with opposite signs, leading to a greater displacement of the envelope. Consequently, the sensitivity of the sensor is further enhanced without altering the harmonic order. Firstly, we conducted numerical simulations to analyze the enhanced harmonic Vernier effect. Secondly, we fabricated a Fabry–Perot interferometer (FPI) and a Mach–Zehnder interferometer (MZI) with strain sensitivity of opposite signs, generating a first-order harmonic. The experimental results indicate that the sensor’s sensitivity is 15.1 pm/μϵ, which is 1.41 and 2.80 times higher than the traditional harmonic Vernier effect using FPI and MZI as sensing interferometers, respectively. The proposed sensor and enhancement method hold promising potential for applications in high-sensitivity measurement fields.

A Pipeline Intrusion Detection Method Based on Temporal Modeling and Hierarchical Classification in Optical Fiber Sensing

A Pipeline Intrusion Detection Method Based on Temporal Modeling and Hierarchical Classification in Optical Fiber Sensing

Study on the Effects of Organic Bonding Agent and Low-Temperature Glass Solder Process on the Performance of Compact Packaged Fiber Optic Temperature Sensors

Study on the Effects of Organic Bonding Agent and Low-Temperature Glass Solder Process on the Performance of Compact Packaged Fiber Optic Temperature Sensors

Quantitative monitoring of localized pitting corrosion in steel bars through a combined use of distributed optical fiber sensors and finite element analyses

Pitting corrosion of steel bars can greatly impair mechanical properties of steel bars, so detecting pitting corrosion timely and accurately is crucial for assessing the health of structures. However, most current corrosion detection methods have some difficulties measuring pitting corrosion level of steel bars effectively. Considering that corrosion pits can cause strain redistribution of steel bar in the tensile state, this study proposes a method to quantitatively determine the pitting corrosion level through monitoring the steel strain distribution. Distributed optical fiber sensors (DOFS) based on Rayleigh scattering and capable of achieving the spatial resolution in millimeter scale were adopted to monitor the strain distributions of notched HRB400E steel bars subjected to tensile stress, and finite element (FE) method was employed to analyze the strain distributions of steel bars with different pit geometries. Experimental results showed that the bare fiber sensors (PI-FS) measured steel strain more accurately than jacketed fiber sensors. From strain distributions monitored by PI-FS, the pit location and pit length can be directly determined. Further, FE results revealed that the strain distribution along the fiber sensor position was significantly affected by the fiber sensor position relative to the pit mouth. Finally, the procedures to determine the pitting corrosion level from DOFS data and FE results were presented by mathematically comparing the similarity of strain curves given by the fiber sensor on a pitting-corroded bar and FE analyses of steel bars with different corrosion levels. In the end, the issues related to the practical applicability of the proposed method were discussed and limitations of this study were addressed. Although with limitations, this study provided a novel and promising way to quantitatively monitor the pitting corrosion level based on the strain distribution of steel bars.

Research on the application of interferometric optical fiber sensors in high-pressure gas pipelines

The advantages of fiber optic sensors based on fiber optic interferometers with explosion-proof safety in gas pipeline monitoring has gradually emerged. A monitoring system for natural gas pipelines was designed and implemented using a Michelson interferometer as the core structure of the fiber optic sensor and processed the collected data using phase carrier generation demodulation algorithms. Addressing practical issues such as phase wrapping and arm length difference losses, an improved phase carrier demodulation algorithm based on tangent transformation and arctangent-differential self-cross-multiplication was proposed. Field experiments were conducted in gas valve chambers, to analyze the characteristics of leak signals in the pipeline. This study lays the foundation for the application of fiber optic interferometer sensors in gas pipeline monitoring, promising enhanced safety and efficiency.